Just 27% of firms are increasing their generative AI budgets in 2025. Last year, that number was 53%.
Your uncertainty about agentic AI isn't a weakness. It's intelligence.
The market is revealing something most executives won't admit: we're all betting blind on autonomous digital workers. The difference is that smart money recognizes the bet for what it is.
The Great AI Pullback
Nearly eight in ten companies report using generative AI. Yet just as many report no significant bottom-line impact.
This creates what researchers call the "gen AI paradox." All that energy, investment, and potential surrounding the technology hasn't materialized into measurable results for most organizations.
The budget cuts reflect this reality. Among firms reporting strong ROI, half are increasing spend. Among firms with negligible ROI, that number drops to 17%.
Your enterprise isn't falling behind by hesitating. You're avoiding the trap that caught early adopters.
Gartner predicts over 40% of agentic AI projects will be canceled by the end of 2027. The reasons? Escalating costs, unclear business value, and inadequate risk controls.
Many use cases positioned as "agentic" today don't actually require agentic implementations. They're experiments driven by hype rather than business necessity.
Who's Really Winning
While enterprises pull back on AI budgets, a different category of company is experiencing explosive growth.
Specialized cloud infrastructure providers are capitalizing on the implementation gap. CoreWeave posted a stunning 420% year-over-year revenue increase. Nebius grew 385%.
These companies aren't building agentic AI systems. They're building the foundation that makes those systems possible.
The real money flows toward solving fundamental infrastructure problems, not toward deploying autonomous agents. Your hesitation about agentic AI reflects a deeper truth: most organizations aren't ready for the infrastructure requirements.
Spending on AI infrastructure is expected to top $200 billion by 2028. The companies securing critical bottleneck resources are positioning themselves as the essential layer between AI ambition and AI reality.
Nebius became the first cloud provider to offer NVIDIA's latest Blackwell superchips in Europe. That's not about agentic AI capability. That's about controlling access to the computational power that makes any AI possible.
The Data Reality Check
Your uncertainty about agentic AI benefits stems from a fundamental infrastructure problem that most vendors won't discuss.
AI agents are only as good as the data feeding them. Most organizations' data is scattered, siloed, unclean, and lacking consistent lineage.
This explains why 80% of organizations pay for subscriptions to tools like ChatGPT or Microsoft Copilot rather than building autonomous systems. For most enterprises, AI adoption in 2025 means consuming prebuilt AI services, not standing up agentic AI platforms.
The gap between agentic AI potential and enterprise adoption isn't about vision or investment. It's about data infrastructure readiness.
Risk-tolerant companies with little to lose can experiment with agentic systems because they're not constrained by existing data architecture. They can build from scratch.
Your enterprise likely can't. And that's not a failure of leadership or imagination.
The Leadership Gap
Fewer than 30% of companies report that their CEOs sponsor their AI agenda directly. This reveals why organizational transformation necessary for agentic success remains elusive.
Agentic AI isn't a technology implementation. It's workforce transformation. It requires C-suite vision and careful integration that addresses both business requirements and employee considerations.
Most AI initiatives remain IT projects rather than business transformation initiatives. Without CEO sponsorship, agentic AI pilots become expensive experiments that never scale.
Your hesitation about agentic AI might reflect this leadership gap. If your CEO isn't directly sponsoring the AI agenda, you're right to question whether autonomous digital workers will deliver promised benefits.
The Edge Alternative
While enterprises struggle with agentic AI adoption, edge AI represents a different pathway forward.
The global edge AI market is projected to reach $66.47 billion by 2030, growing at 21.7% annually. By 2027, an estimated 62% of data will be processed on edge devices.
Edge AI enables intelligent capabilities without massive infrastructure investment. It democratizes access to AI benefits without requiring the organizational transformation that agentic systems demand.
This might be where your enterprise finds its AI advantage. Not through autonomous digital workers, but through intelligent capabilities embedded in existing workflows and devices.
Your Strategic Response
The agentic AI adoption gap isn't a problem to solve. It's market intelligence to leverage.
Risk-tolerant companies with nothing to lose will continue experimenting with autonomous digital workers. Some will succeed. Most will join the 40% of canceled projects.
Your uncertainty positions you to learn from their experiments without bearing their costs.
Deloitte predicts 25% of companies using generative AI will launch agentic AI pilots in 2025, growing to 50% in 2027. But the "autonomous" part may take time for wide adoption.
Focus on understanding which workflows can and should be agentized for measurable ROI. Develop your AI strategy from there, not from technological capability.
The companies succeeding with AI aren't the ones with the biggest budgets or the most advanced pilots. They're the ones with the clearest understanding of where AI creates genuine business value.
Your skepticism about agentic AI hype isn't holding you back. It's keeping you grounded while others chase expensive experiments.
The autonomous digital workforce is coming. But it's not here yet, and pretending otherwise is how budgets get slashed and projects get canceled.
Stay curious. Stay skeptical. And let the risk-tolerant companies show you what actually works.
